- Open Access
Benchmarking dark matter search using a parity-check protocol with machine-learning optimized pulses
Phys. Rev. D 114, 052011 – Published 17 September, 2026
DOI: https://doi.org/10.1103/m92t-xwgt
Abstract
We report on an improved microwave detection protocol for dark matter candidates such as the axion and the dark photon. We employ a superconducting transmon qubit dispersively coupled to a double-cavity system, enabling quantum nondemolition measurements of the photon occupation in a relatively short-lived storage cavity. To reduce the experimental cycle time and enhance sensitivity for axion and dark photon searches, we operate this detector in a regime of increased qubit–cavity coupling, resulting in Stark shifts of 4.6 MHz. In this regime, conventional control pulses suffer from strong frequency-detuning sensitivity and photon-number-dependent errors. We address this limitation by implementing frequency-detuning-robust pulses (obtained by machine-learning optimization) that preserve high-fidelity qubit control over a bandwidth of approximately 20 MHz. We experimentally validate this protocol and demonstrate single-photon detection performance comparable to previous implementations, despite significantly reduced qubit coherence times and storage-cavity lifetimes. Using parity-based measurement sequences combined with a hidden Markov model (HMM) analysis, we achieve background rates on the order of . In the absence of a magnetic field, we derive exclusion limits on the dark photon model for dark matter, reaching a sensitivity to the kinetic mixing angle of at 5.051 GHz. These results establish machine-learning-robust control as a key enabler for faster, more scalable microwave quantum sensors for dark matter searches.
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